Tag: Availability

OEE: Planned Downtime and Availability

Injection Molding Press
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As a core metric, Overall Equipment Effectiveness or OEE has been adopted by many companies to improve operations and optimize the capacity of existing equipment.  Having completed several on site assessments over the past few months we have learned that almost all organizations are measuring performance and quality in real-time, however, the availability component of OEE is still a mystery and often misunderstood – specifically with regard to Set Up or Tool Changes.

We encourage you to review the detailed discussion of down time in our original posts “Calculating OEE – The Real OEE Formula With Examples” and “OEE, Down time, and TEEP” where we also present methods to calculate both OEE and TEEP.  The formula for Overall Equipment Effectiveness is simply stated as the product of three (3) elements:  Availability, Performance, and Quality.  Of these elements, availability presents the greatest opportunity for improvement.  This is certainly true for processes such as metal stamping, tube forming, and injection molding, to name a few, where tool changes are required to switch from one product or process to another.

Switch Time

Set up or change over time is defined as the amount of time required to change over the process from the last part produced to the first good part off the next process.  We have learned that confusion exists as to whether this is actually planned down time as it is an event that is known to occur and is absolutely required if we are going to make more than one product in a given machine.

Planned down time is not included in the Availability calculation.  As such, if change over time is considered as a planned event, the perceived availability would inherently improve as it would be excluded from the calculation.  Of course, the higher availability is just an illusion as the lost time was still incurred and the machine was not available to run production.

If we could change a process at the flip of a switch, set up time would be a non-issue and we could spend our time focusing on other improvement initiatives.  While some processes do require extensive change over time, there is always room for improvements.  This is best exemplified by the metal stamping industry where die changes literally went from Hours to Minutes.

To remain competitive and to increase the available capacity, many companies quickly adopted SMED (Single Minute Exchange of Dies) initiatives after recognizing that significant production capacity is being lost due to extensive change over times.  Overtime through extended shifts and capital for new equipment is also reduced as capacity utilization improves.

Significantly reduced inventories can also be realized as product change overs become less of a concern and also provide greater flexibility to accommodate changes in customer demand in real-time.  Significantly increased Inventory Turns will also be realized in conjunction with net available cash from operations.

Redefining Down Time

The return on investment for Quick Tool Change technologies is relatively short and the benefits are real and tangible as demonstrated through the metrics mentioned above.  Rather than attempt to categorize down time as either planned or unplanned, consider whether the activity being performed is impeding the normal production process or can be considered as an activity required for continuing production.

We prefer to classify down time as either direct or indirect.  Any down time such as Set Up, Material Changes, Equipment Breakdowns, Tooling Adjustments, or other activity that impedes production is considered DIRECT down time.  Indirect down time applies to events such as Preventive Maintenance, Company Meetings, or Scheduled IDLE Time.  These events are indeed PLANNED events where the machine or process is NOT scheduled to run.

Redefine the Objective

Set up or change over time is often the subject of much heated debate and tends to create more discussion than is necessary.  The reason for this is simple.  Corporate objectives are driven by metrics that measure performance to achieve a specific goal.

Unfortunately, in the latter case, the objectives are translated into personal performance concerns for those involved in the improvement process.  Rather than making real improvements, the tendency is to rationalize the current performance levels and to look for ways to revise the definition that creates the perception of poor performance. Since availability does not include planned down time, many attempts are made to exclude certain down time events, such as set up time, to create a better OEE result than was actually achieved.

Attempts to rationalize poor performance inhibits our ability to identify opportunities for improvement.  From a similar perspective, we should also be prudent with. and cognizant of, the time allotted for “planned” events.

It is for this reason that some companies have resorted to measuring TEEP based on a 24 hour day.  In many respects, TEEP eliminates all uncertainty with regard to availability since you are measured on the ability to produce a quality part at rate.  As such, our mission is simple – “To Safely Produce a Quality Part At Rate, Delivered On Time and In Full”.  Any activity that detracts from achieving or exceeding this mission is waste.

Remember to get your OEE spreadsheets at no charge from our Free Downloads Page or Free Downloads Box in the sidebar.  They can be easily and readily customized for your specific process or application.

Please feel free to send your comments, suggestions, or questions to Support@VergenceAnalytics.com

Until Next Time – STAY lean!

Vergence AnalyticsVergence Analytics
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OEE for Batch Processes

Coke being pushed into a quenching car, Hanna ...
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We recently received an e-mail regarding OEE calculations for batch processes and more specifically the effect on down stream equipment that is directly dependent (perhaps integrated) on the batch process.  While the inquiry was specifically related to the printing industry, batch processing is found throughout manufacturing. Our more recent experiences pertain to heat treating operations where parts are loaded into a stationary fixed-load oven as opposed to a continuous belt process.

Batch processing will inherently cause directly integrated downstream equipment (such as cooling, quenching, or coating processes) to be idle. In many cases it doesn’t make sense to measure the OEE of each co-dependent piece of equipment that are part of the same line or process. Unless there is a strong case otherwise, it may be better to de-integrate or de-couple subsequent downstream processes.

Batch processing presents a myriad of challenges for line balancing, batch sizes, and capacity management in general.  We presented two articles in April 2009 that addressed the topic of  where OEE should be measured.  Click here for Part I or Click  here for Part II.

Scheduling Concerns – Theory of Constraints

Ideally, we want to measure OEE at the bottleneck operation.  When we apply the Theory of Constraints to our production process, we can assure that the flow of material is optimized through the whole system.  The key of course is to make sure that we have correctly identified the bottleneck operation.  In many cases this is the batch process.

While we are often challenged to balance our production operations, the real goal is to create a schedule that can be driven by demand.  Rather than build excess inventories of parts that aren’t required, we want to be able to synchronize our operations to produce on demand and as required to keep the bottleneck operation running.  Build only what is necessary:  the right part, the right quantity, at the right time.

Through my own experience, I have realized the greatest successes using the Theory of Constraints to establish our material flows and production scheduling strategy for batch processes.  Although an in-depth discussion is beyond the scope of this article, I highly recommend reading the following books that convey the concepts and application through a well written and uniquely entertaining style:

  1. In his book “The Goal“, Dr. Eliyahu A. Goldratt presents a unique story of a troubled plant and the steps they took to turn the operation around.
  2. Another book titled “Velocity“, from the AGI-Goldratt Institute and Jeff Cox also demonstrates how the Theory of Constraints and Lean Six Sigma can work together to bring operations to all new level of performance, efficiency, and effectiveness.

I am fond of the “fable” based story line presented by these books as it is allows you to create an image of the operation in your own mind while maintaining an objective view.  The analogies and references used in these books also serve as excellent instruction aids that can be used when teaching your own teams how the Theory of Constraints work.  We can quickly realize that the companies presented in either of the above books are not much different from our own.  As such, we are quickly pulled into the story to see what happens and how the journey unfolds as the story unfolds.

Please leave your comments regarding this or other topics.  We appreciate your feedback.  Also, remember to get your free OEE spreadsheets.  See our free downloads page or click on the file you want from the “Orange” box file on the sidebar.

Until Next Time – STAY lean!

Vergence AnalyticsVergence Analytics

Benchmarking OEE

Benchmarking Systems:

We have learned that an industry standard or definition for Overall Equipment Effectiveness (OEE) has been adopted by the Semi Conductor Industry and also confirms our approach to calculating and using OEE and other related metrics.

The SEMI standards of interest are as follows:

  • SEMI E10:  Definition and Measurement of Equipment Reliability, Availability, and Maintainability.
  • SEMI E35:  Guide to Calculate Cost of Ownership Metrics.
  • SEMI E58:  Reliability, Availability, and Maintainability Data Collection.
  • SEMI E79:  Definition and Measurement of Equipment Productivity – OEE Metrics.
  • SEMI E116:  Equipment Performance Tracking.
  • SEMI E124:  Definition and Calculation of Overall Factory Efficiency and other Factory-Level Productivity Metrics.

It is important to continually learn and improve our understanding regarding the development and application of metrics used in industry.  It is often said that you can’t believe everything you read (especially – on the internet).  As such, we recommend researching these standards to determine their applicability for your business as well.

Benchmarking Processes:

Best practices and methods used within and outside of your specific industry may bring a fresh perspective into the definition and policies that are already be in place in your organization.  Just as processes are subject to continual improvement, so are the systems that control them.  Although many companies use benchmarking data to establish their own performance metrics, we strongly encourage benchmarking of best practices or methods – this is where the real learning begins.

World Class OEE is typically defined as 85% or better.  Additionally, to achieve this level of “World Class Peformance” the factors for Availability, Performance, and Quality must be at least 90%, 95%, and 99.5% respectively.  While this data may present your team with a challenge, it does little to inspire real action.

Understanding the policies and methods used to measure performance coupled with an awareness of current best practices to achieve the desired levels of  performance will certainly provide a foundation for innovation and improvement.  It is significant to note that today’s most efficient and successful companies have all achieved levels of performance above and beyond their competition by understanding and benchmarking their competitors best practices.  With this data, the same companies went on to develop innovative best practices to outperform them.

A Practical Example

Availablity is typically presented as the greatest opportunity for improvement.  This is even suggested by the “World Class” levels stated above.  Further investigation usually points us to setup / adjustment or change over as one of the primary improvement opportunities.  Many articles and books have been written on Single Minute Exchange of Dies and other Quick Tool Change strategy, so it is not our intent to present them here.  The point here is that industry has identified this specific topic as a significant opportunity and in turn has provided significant documentation and varied approaches to improve setup time.

In the case of improving die changes a variety of techniques are used including:

  • Quick Locator Pins
  • Pre-Staged Tools
  • Rolling Bolsters
  • Sub-Plates
  • Programmable Controllers
  • Standard Pass Heights
  • Standard Shut Heights
  • Quarter Turn Clamps
  • Hydraulic Clamps
  • Magnetic Bolsters
  • Pre-Staged Material
  • Dual Coil De-Reelers
  • Scheduling Sequences
  • Change Over Teams versus Individual Effort
  • Standardized Changeover Procedures

As change over time becomes less of a factor for determining what parts to run and for how long, we can strive reduced inventories and improved preventive maintenance activities.

Today’s Challenge

The manufacturing community has been devastated by the recent economic downturn.  We are challenged to bring out the best of what we have while continuing to strive for process excellence in all facets of our business.

Remember to get your free Excel Templates by visiting our FREE Downloads page.  We appreciate your feedback.  Please leave a comment an email to leanexecution@gmail.com or vergence.consultin@gmail.com

Until Next Time – STAY Lean!

How OEE can improve your Inventory

Once you have established a robust OEE system, you should also be reaping benefits in other areas of your organization.

We will be offering some insights into the other performance metrics such as inventory over the next few weeks. Improved availability, performance, and quality will all have an impact on your inventory and materials management processes. Inventory turns is one metric that should be improving as your OEE improves. If not, perhaps there is an opportunity to integrate OEE even deeper into your organization.

In a truly lean organization, other vantage point metrics will provide evidence of a well integrated OEE system. Metrics such as delivery, quality (ppm), labour efficiency, lead time, mean time between failures, mean response times, down time, turn over, and financial performance indicators are all directly or indirectly affected by improvements to your operation and OEE.

We will discuss the impact of OEE on these “other” metrics over the next few posts. Remember, we also offer excel templates at no cost to you. Click on the “BOX” files on the sidebar to get your free templates today! Our templates offer more than a simple OEE calculator – they can be used immediately with little or no modifications to suit your processes.

Until next time, STAY lean!

Vergence – Lean Execution Team.

OEE Integration: Can you fix it?

As we are all aware, inspecting or measuring parts does not change the quality of the product.   Likewise, measuring and reporting OEE alone does not solve problems or improve performance.  While it is fair to say that increased focus and measurement of any process usually results in some degree of improvement, these are typically attributed to changes in human behavior due to observation and not necessarily real process improvements.

Using OEE to identify opportunities in your operation is the equivalent of turning the light on in a dark room.  Although the room hasn’t changed, we certainly have a better understanding of what it looks like.  As such, OEE is a vantage point metric that can be used to illuminate our understanding of the process and identify opportunities to drive improvements.

It is essential for your team to develop and utilize effective problem solving skills to successfully identify systemic and process root causes for failure and to develop and execute permanent corrective actions to resolve them.  Our experience suggests that the lack of solid and proven problem solving skills coupled with poor execution is the leading cause of failure for new initiatives such as OEE.

We introduced an approach to improving OEE in our “Improve OEE:  A Hands On Approach“, post (03-Jan-09).  Although we identified some of the tools that could be used to solve of the problems, we didn’t spend much time going into the details.  Over the next few posts, we’ll discuss some of the ideas in a little more detail.

The real problem for most companies is identifying what the real underlying root cause of the current “failure” mode is.  Without a good understanding of the root cause, the solutions developed and implemented will not be effective, only serving to temporarily cure the immediate superficial symptoms.

Using effective problem solving skills to analyze the OEE data and to develop and execute permanent corrective actions will assure sustainable and ever improving performance.

Until Next Time – STAY lean!

OEE Integration – Where do We Measure OEE? – Part I

OEE Integration Part IX – Where do we measure OEE?

Our recent posts have included numerous examples to calculate OEE correctly. We also discussed integration of OEE as an effective metric for managing your processes and ultimately how to analyze and use the data to improve your profitability.  We spent little time discussing where this measurement should occur.  OEE can be measured for both manual and automated lines as well as any stand alone operation.

The OEE factors (Performance, Availability, and Quality) are process output results.  The expectation, of course, is to manage the inputs to the process to assure the optimal result is achieved.  Availability, Performance, and Quality can be measured in real-time during production. However, the results should be subject to a due diligence review when production is complete.

At a minimum, it makes sense to measure OEE at the end (output) of the line or process but this is not always ideal.  The complexity of OEE measurement occurs when single or multiple sub-cells are constrained by an upstream or downstream operation or bottleneck operation.  The flow, rate, or pace of a process is always  restricted or limited by a  sequence / process constraint or bottleneck operation.  Just as a chain is only as strong as its weakest link, so too is the line speed limited by the bottleneck operation.

We contend that the “Control-Response” loop for any process must enable immediate and effective corrective action based on the measured data and observations.  Measuring OEE in real-time at the bottleneck process makes it an ideal “Trigger Point” metric or “Control-Response” metric for managing the overall process even in “isolation” at the bottleneck operation.  Any variations at the bottleneck correlate directly to upstream and downstream process performance.

A disruption to production flow may occur due to a stock-out condition or when a customer or supplier operation is down.  While these situations affect or impact the OEE Availability factor, external factors are beyond the scope of the immediate process.

Real-time OEE requires that these events and others, such as product disposition, are reported in real-time as well.  External events are more difficult to capture in real-time and by automated systems in particular.  Operator interfaces must accommodate reporting of these events as they occur.

Reporting PITFALL – After-the-Fact events

If a quality defect is discovered several days after reporting production and all parts are placed on hold for sorting or rework, the QUALITY Factor for that run should be changed to ZERO.  In turn, the net OEE for that run will also be ZERO.  If the system is not changed, the integrity of the data is lost.  This also exemplifies that real-time data can be deceiving if proper controls are not in place.

“Where do we measure?” is followed by “When do we measure?” The short list of examples provided here are likely events that are far and few between.  If this is a daily occurrence, consider adopting the banking policy of, “adjustments to your account will be reflected on the following business day”.  Your process / system is in need of a rapid fix.

OEE is one of the few vital signs or key performance metrics for your manufacturing operation.  As such, measure where you will reap the greatest benefit and focus your attention on the process or operation accordingly.  OEE is as much a diagnostic tool as it is a monitoring tool.

Until Next Time – STAY lean!

Vergence Analytics
Versalytics

OEE: Take the Hit

The simplicity of measuring and calculating OEE is compounded by the factors that ultimately influence the end result.  Because the concept of OEE can be readily embraced by most employees, it is easy for many people to get involved in the process of making improvements.

Unfortunately the variables involved with OEE, like those of many other measurement systems, fall under scrutiny.  The goal of achieving yet even higher OEE numbers is met with yet another review of the factors and how they are treated.  Usually the scope of this often heated discussion is focused on Availability.

The greatest task of all occurs when attempting to classify what qualifies as planned versus unplanned downtime.  Availability is the primary factor where significant improvements can be realized and is most certainly the focus of every TPM program in existence.  However, another significant factor that can greatly impact Availability is setup time.

We still receive questions and comments from our readers regarding setup time and whether or not they should “take the hit” for it.  We have met up with different rationale and reasoning to exclude setup time from the availability factor such as:  “We have all kinds of capacity and do the setups in our free time.” Or, “We do the setups on the off shift so the equipment is always ready when the first shift comes in.”

Regardless of the rationale, our short answer to the question of inclusion for setup time remains a simple, “Yes, take the hit.”  Before we get to much further let’s define what it is.  Setup time is typically defined as the time required to change or setup the next process.  The duration of time is measured from the last good part produced to the first good part produced from the new process.

Improving setup times provides for shorter runs, reduced inventories, increased available capacity, increased responsiveness, improved maintenance, and in turn, improved quality.  Shorter runs also provide the opportunity to maintain tools more effectively between runs as they are not as subject to excessive wear caused by longer run times and higher production levels.

Setup and Quick Die Change / Quick Tool Change

An exhaustive amount of work has been completed in many manufacturing disciplines to reduce and improve setup times.  Certainly, by simply ignoring the setup time, there is no real way to determine whether the new methods are having an impact unless another measurement system for setup is introduced.  We already have a measurement system in place, so why invent another one?

Quick Die Change and other Quick Tool Change strategies are common place in industries such as automotive stamping plants.  The objectives for Quick Die Change are attributed to LEAN principles such as single part flow and reduced inventories.  The benefits of these efforts, of course, extend to OEE and availability.

Setup and Production Sequencing

To exemplify the effect of sequencing and setup, consider a single tool that makes 8 variations of a product.  For the sake of discussion, let’s assume the only difference is the number of holes punched into the part.  The time for each punch removed from, or added to, the tool is the same.

The objective for scheduling this tool is quite obvious.  We need to minimize the number of punch changes to minimize the downtime.  If the parts required range from 1 hole to 8 holes, and we need 100 parts of each variant, we would arrange the schedule in such a manner as to make sure we are only adding one punch to the tool as we move on to the next variant.

In this case, setup time and sequencing are clearly a cause for concern and consideration.  Secondly, it is much easier to calculate the time required to run all the parts and how much capacity is required.  Including setup in the OEE factor also simplifies the calculation of overall capacity utilization for the piece of equipment in general.

In Conclusion

As we have stated in previous posts, the objective of measuring OEE is to identify opportunities for improvement.  Achieving higher numbers through the process of debate and elimating elements for consideration is not making improvements.  Don’t masquerade the problem or the opportunities. 

Setup is certainly one area where improvements can be measured and quantified.  Availability and OEE results provide an opportunity to demonstrate the effectiveness of these improvements accordingly.

If the leadership of the company is setting policy then the explanations for performance in this regard should be understood.  The only numbers that really matter are on the bottom line and hopefully they are black.

We would also encourage you to visit two of our recent posts, Improving OEE – A hands on approach (posted 03-Jan-09) and OEE and Availability, (posted 31-Dec-2008).

Until next time, stay LEAN.